{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"萌喵读文献-肿瘤学","title":"今日肿瘤学最高分文献 - 2025-10-25","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/007a4969\"></iframe>","width":"100%","height":180,"duration":184,"description":"科研喵使用ai读文献，祝你效率百倍，访问labcat.com.cn下载。\n\n今天我们关注一项发表在《Computers in Biology and Medicine》(影响因子7.0)上的重要研究，标题为\"Artificial Intelligence and radiomics models for the diagnosis and prognosis of peritoneal metastases on imaging: a systematic review and meta-analysis\"。这项系统性回顾和荟萃分析评估了AI和放射组学模型在腹膜转移(PM)影像学诊断和预后中的性能。研究显示，13项研究的荟萃分析得出PM检测的综合AUC为0.84，敏感性0.75，特异性0.80。2D和3D影像数据表现相当，而将临床因素纳入模型可显著提高性能。这项发现为AI辅助癌症诊断开辟了新途径，有望改善腹膜转移患者的早期检测和个性化治疗决策。","thumbnail_url":"https://img.transistorcdn.com/3WX36CzvFOrNjlF7WfWjzS4HdcMIMmzMs2bmPS-ejLU/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83NDNm/MjQ1N2E5NjhjMzVj/NjM0ZTA3YzY2NDE2/ZmIyMi5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}